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data analysis of the National database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) Open data Japan with an adjustment of confounding factors

Data analysis of the National Database of Health Insurance C...

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8th ieee asia-pacific conference on computer science and data engineering (ieee csde)

作者： Ishii, Kazuo Nishio, Takuya Itoigawa, Yuta Sakaki, Seigo Sakagami, Ryuji Shoji, Yoshihisa Fukumoto, Yoshihiro Suwa Univ Sci Fac Engn Dept OfAppl Informat Engn Chino Nagano Japan Fukuoka Dent Coll Dept Odontol Sect Periodontol Fukuoka Japan Kurume Univ Sch Med Dept Neuropsychiat Cognit & Mol Res Inst Brain Dis Kurume Fukuoka Japan Kurume Univ Sch Med Dept Internal Med Div Cardiovasc Med Kurume Fukuoka Japan

ISBN: (纸本)9781665495523

National database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) Open data Japan publishes summary tables of fundamental data from NDB. In this report, we performed a pilot study on the mental health and dental care of patients with noncommunicable diseases (NCDs) using NDB Open data Japan. We performed data analysis using the Sex- and Age-Standardized Regional Difference Index (SA-RDI) to preliminarily show the relationship between diabetes mellitus and periodontal disease. Consequently, we could visualize the relationship between them at the prefectural (community) level.

关键词： NDB NDB Open data Japan Sex- and Age-Standardized Regional Difference Index (SA-RDI) relationship visualization

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Understanding Facial Expression of Children with Autism Using Learning Theory

Understanding Facial Expression of Children with Autism Usin...

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Anushka Zaman Evea Zerin Khan Md. Golam Rabiul Alam Amitabha Chakrabarty Dept. of Computer Science and Engineering BRAC University Dhaka Bangladesh

It is challenging for autistic individuals to gather socially and empathically, as we understand, so this subject matter differs from the identification of a common human facial expression. In our research, we have taken pictures of children and teenagers from school of special children based in Bangladesh, aged between 5 to 20 with Autism Spectrum Disorder (ASD) and identified their emotions from their images. Our objective is to find a technique that will allow their emotions to be accurately perceived and thus, make it easy for them including other individuals around them to interact socially without any barriers. In our paper, we implemented VGG16 and six Machine Learning Algorithms along with one Feature Extraction technique to detect Facial Expression of children with autism. The proposed system has showcased an accuracy of 75% for VGG16, 68% for Random Forest Classifier, 61% for Random Forest Classifier along with PCA, 61% for Support Vector Machine (SVM) and 67% for SVM with PCA, 56% for Logistic Regression and 53% for Logistic Regression along with PCA, 52% for Linear Discriminant Analysis (LDA) and 54% for LDA with PCA, 46% for Decision Tree and 50% for Decision Tree along with PCA and 46% for Gaussian Naïve Bayes and 38% for Gaussian Naïve Bayes along with PCA.

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Signal Modulation Recognition Method Based on Residual Connection SWT-LSTM 11

Signal Modulation Recognition Method Based on Residual Conne...

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11th ieee asia-pacific conference on Antennas and Propagation, APCAP 2023 - Proceedings

作者： Bai, Neng Ye, Fang Zhang, Hedan Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Nanjing University School of Electronic Science and Engineering Nanjing210023 China

ISBN: (纸本)9798350326277

In response to the problem of low signal modulation recognition rate under low signal-to-noise ratio(SNR), this paper proposes a modulation recognition method based on residual connection SWT-LSTM. The algorithm inputs IQ signal data into the network and utilizes the SWT-LSTM network layer to extract signal features and achieve modulation recognition. The connection between SWT and residual can improve the network's ability to extract useful features and improve recognition rate under low SNR. The simulation results show the excellent performance of the algorithm, and the recognition rate of the proposed recognition model is higher than that of other algorithms. © 2023 ieee.

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Orchestrating the Resilience of Cloud Microservices Using Task-Based Reliability and Dynamic Costing

Orchestrating the Resilience of Cloud Microservices Using Ta...

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Vyas O'Neill Ben Soh Department of Computer Science and Information Technology La Trobe University Melbourne Australia

In recent years, cloud computing has grown in popularity as enterprises realize the technical and economic benefits of managing resources using an on-demand model. With this growth come user expectations of quality of service, availability and reliability. As the trend in cloud systems architecture moves from monolithic systems to microservices, opportunities exist to develop granular solutions for improving the reliability of the overall system. In this paper we propose an approach to the resilience of microservices-based cloud systems using task-based reliability, quantifying of the reliability requirement with respect to the marginal cost of additional redundancy and the cost of failure. Our approach enables the cloud orchestrator to manage replication of microservice containers to reach an optimal, cost-effective level of redundancy. Empirical testing showed our approach achieved a lower overall cost in comparison with a fixed-reliability approach under an exponential failure function.

关键词： Cloud computing Costs Costing Redundancy Microservice architectures Reliability engineering Reliability

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Braille-to-Chinese Translation System Based on Optical Braille Recognition 2

Braille-to-Chinese Translation System Based on Optical Brail...

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2nd asia-pacific conference on Communications Technology and computer science, ACCTCS 2022

作者： Shao, Zirui Yu, Zhi Gu, Yu Wang, Wei School of Software Technology Zhejiang University Hangzhou China College of Computer Science Zhejiang University Zhejiang Provincial Key Laboratory of Service Robot Hangzhou China

ISBN: (纸本)9781665400343

Braille is an essential tool for visually impaired people to receiving and transmitting information. However, sighted people without special training cannot read Braille, which will cause inconvenience to scenarios such as special education that require sighted people to read Braille. This paper implements a Braille-to-Chinese translation system composed of optical Braille recognition, Braille-to-pinyin conversion, and pinyin-to-character module. Experiments prove that our system can effectively and accurately translate Braille images into Chinese. Our system has broad application prospects, which can help the sighted people read Braille and help visually impaired people in their study and life. © 2022 ieee.

关键词： Training computer science Braille Visualization Optical imaging Communications technology

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Towards Recoverability-Oriented Cloud Operations 2

Towards Recoverability-Oriented Cloud Operations

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2nd asia-pacific conference on Communications Technology and computer science, ACCTCS 2022

作者： Liu, Daijiao Fu, Min Beijing University of Science and Technology Beijing China Macquarie University Sydney Australia

ISBN: (纸本)9781665400343

The dependability of consumer-initiated cloud operations has become a hot research topic in the field of cloud computing. Such a cloud operation's dependability can be achieved by enabling its recoverability, e.g. applying recovery actions for errors during cloud operations. In order to facilitate cloud operations' recoverability, one way is to design more recoverability-oriented cloud operations. Cloud operations designed with more effective recoverability-oriented characteristics can receive recovery actions by a recovery service with ease. In this paper, we propose a methodology of how to make such kind of cloud operations. Specifically, the methodology contains three steps: 1) operation prototype design;2) cloud resources analysis;3) operation prototype transformation. We demonstrate our methodology by using the widely used rolling upgrade operation on AWS Cloud. © 2022 ieee.

关键词： Recovery

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Performance Analysis of Machine Learning Algorithms for Classification of Infection Severity Levels on Rubber Leaves

Performance Analysis of Machine Learning Algorithms for Clas...

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Siti Saripa Rabiah Mat Lazim Zulkefly Sulaiman Nazmi Mat Nawi Anas Mohd Mustafah Institute of Plantation Studies Universiti Putra Malaysia Department of Plant Science Faculty of Agriculture Unversiti Putra Malaysia Serdang Malaysia Department of Biological and Agricultural Engineering Universiti Putra Malaysia Selangor Malaysia

White root disease (WRD) infection in rubber plantations which is caused by Rigidiporus micropores can lead to a significant yield loss. At the early infection stage, it is very difficult to diagnose the disease because infected trees do not exhibit any symptoms. Thus, this study was carried out to investigate the potential application of spectroscopic technology and machine learning algorithms to classify severity level of infected trees at early stage based on spectral data. A total of 50 leaf samples were used in this work, representing five severity levels; healthy, light, moderate, severe and very severe infection. A visible shortwave near-infrared (VSNIR) spectrometer was used to record the spectral data of the leaf samples. The chlorophyll content of each leaf was measured using SPAD meter. Four classification algorithms investigated in this study were artificial neural network (ANN), support vector machine (SVM), knearest neighbour (kNN) and random forest (RF). The result of the study demonstrates good classification accuracy of 90, 82, 78, and 72% for ANN, SVM, kNN and RF, respectively. This work shows that the spectroscopic measurement combined with classification techniques are promising strategy to classify severity level of WRD based on the spectral data of the rubber leaves.

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Multi-target Pedestrian Tracking Based on YOLOv5 and DeepSORT

Multi-target Pedestrian Tracking Based on YOLOv5 and DeepSOR...

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2022 ieee asia-pacific conference on Image Processing, Electronics and computers, IPEC 2022

作者： Wang, Yuhan Yang, Han Shenyang Aerospace University The Database Research Group in School of Computer Science Shenyang China University of Science and Technology Beijing The School of Automation and Electrical Engineering Beijing China

ISBN: (纸本)9781665409025

Target detection and tracking are crucial in autonomous driving and intelligent transportation, especially in pedestrians and traffic safety. The dynamic pedestrian tracking algorithm using YOLOv5 and DeepSORT is proposed to improve accuracy and robustness, based on the classical tracking-by-detection approach, to achieve real-time monitoring and tracking of pedestrians in the video. The YOLOv5 algorithm is used for pedestrian detection in the video. The YOLOv5 algorithm is used to detect the pedestrian targets in the video and calculate the pedestrian distance to assess the risk. The detected pedestrian features are tracked in real-time using the DeepSORT algorithm to complete the pedestrian trajectory tracking. The experimental results show that the method is effective in detecting pedestrians when coping with the problems of abrupt and rapid movement, occlusion, and appearance deformations, which is suitable for online real-time tracking of pedestrians. © 2022 ieee.

关键词： Pedestrian safety

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BanglaSarc: A dataset for Sarcasm Detection

BanglaSarc: A Dataset for Sarcasm Detection

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Tasnim Sakib Apon Ramisa Anan Elizabeth Antora Modhu Arjun Suter Ifrit Jamal Sneha MD. Golam Rabiul Alam Computer Science and Engineering BRAC University Dhaka Bangladesh

Being one of the most widely spoken language in the world, the use of Bangla has been increasing in the world of social media as well. Sarcasm is a positive statement or remark with an underlying negative motivation that is extensively employed in today's social media platforms. There has been a significant improvement in sarcasm detection in English over the previous many years, however the situation regarding Bangla sarcasm detection remains unchanged. As a result, it is still difficult to identify sarcasm in bangla, and a lack of high-quality data is a major contributing factor. This article proposes BanglaSarc, a dataset constructed specifically for bangla textual data sarcasm detection. This dataset contains of 5112 comments/status and contents collected from various online social platforms such as Facebook, YouTube, along with a few online blogs. Due to the limited amount of data collection of categorized comments in Bengali, this dataset will aid in the of study identifying sarcasm, recognizing people's emotion, detecting various types of Bengali expressions, and other domains. The dataset is publicly available at https://***/datasets/sakibapon/banglasarc.

关键词： computer science Emotion recognition Video on demand Social networking (online) Blogs data collection data engineering

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Optimization of Active Layer Morphology for High-Efficiency Layer-by-Layer Organic Solar Cells with 18.13% Efficiency 4

Optimization of Active Layer Morphology for High-Efficiency ...

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4th asia-pacific conference on Communications Technology and computer science, ACCTCS 2024

作者： Yu, Xin Lin, Hui He, Zeyu Du, Xiaoyang Zheng, Caijun Tao, Silu School of Optoelectronic Science and Engineering University of Electronic Science and Technology of China Chengdu610054 China

ISBN: (纸本)9798350359985

The production of organic solar cells (OSCs) employing the layer-by-layer (LbL) casting approach is a very popular method nowadays. However, the diffusion of the acceptor during the LbL film formation process is uncontrollable and limited, which restricts the development of the LbL OSCs performance. To surmount this phenomenon, a novel LbL deposition strategy was adopted in this study. Traces of PY-IT were firstly added to the donor layer DIS-CI to utilize the poor miscibility between the two polymeric materials, which resulted in a blend film with a large phase separation. Subsequently, owing to the favorable miscibility of PY-IT with the acceptor layer material LS-BO, as well as the large phase separation of the DIS-CI:PY-IT film, the diffusion of LS-BO in the donor layer was effectively expanded. This induced a more desirable vertical morphology of active layer, thereby better balancing the charge generation, transport, and collection. For this reason, LbL OSCs based on DIS-CI:PY-IT/LS-BO achieved a power conversion efficiency (PCE) of IS.13%, which is a dramatic improvement versus the device based on DIS-CI/LS-BO (PCE of 17.16%). This study presents a novel and efficacious strategy for building efficient LbL OSCs. © 2024 ieee.

关键词： Organic solar cells

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